Roy E. Williams

Effects of data representation and network architecture variation on multiaperture vision system performance

This research focuses on the effects of data representation and variations in neural network architecture on the tracking accuracy of a multi-aperture vision system (MAVS). A back- propagation neural network (BPNN) is used as a target location processor. Six different MAVS optical configurations are simulated in software. The systems responses to a point source target, in the form of detector voltages, and the known target location form a training record for the BPNN. Neural networks were trained for each of the optical configurations using different coordinate systems to represent the location of the point source target relative to the optical axis of the central eyelet. The number of processing elements in the networks hidden layer was also varied to determine the impact of these variations on the task of target location determination. A figure-of-merit (FOM) for the target location systems is developed to facilitate a direct comparison between the different optical and BPNN models. The results are useful in designing a MAVS tracker.

Study of two different biological insect eye maps with artificial neural network processing

Insect eyes have a large number of facets or lenses, also known as ommatidia or eyelets, with different arrangements of biological photoreceptors coupled to each eyelet. The output of each photoreceptor is coupled to sets of neurons where the optical information is processed. It is interesting to note that different insects are comprised of entirely different visual systems. These varying eyelet arrangements appear to be particular to the insects habits and habitats. To test this premise, two very different insect ommatidia maps coupled to artificial neural network (NN) processors were modeled and simulated on a silicon graphics workstation. The performance of each ommatidia/NN system was tested in point source target location tasks and finite target location tasks in order to compare the two to each other and to man-made multi- aperture vision systems. The results of these simulations are presented.